A leading US-based parking management company faced significant operational inefficiencies due to its reliance on third-party ALPR (Automatic License Plate Recognition) solutions that were difficult to integrate with backend systems. These challenges resulted in frequent validation errors, manual interventions, and poor user experience for parkers.
To address these issues, ekSource developed a custom ALPR and gate vending system, leveraging edge computing on NVIDIA Jetson devices, real-time data processing, and seamless integration with backend reservation systems. The AI-driven solution enabled:
Real-time validation of existing parking reservations by matching license plates with the backend system.
Automated gate vending, eliminating the need for manual validation.
Frictionless entry for non-reservation users, prompting them to create an account after parking.
By building an end-to-end ALPR solution that eliminated reliance on third-party vendors, reduced operational costs, and improved user experience, ekSource delivered a fully integrated, scalable, and cost-efficient solution for the client.
Business Challenge
The client faced multiple challenges with their existing third-party ALPR system, including:
1. Inefficient Backend Integration & Lack of Control
The third-party ALPR solution was not natively integrated with the company’s reservation and payment systems, leading to frequent mismatches and validation failures.
Limited API access and customization options made it difficult to automate business workflows.
Frequent outages and latency issues caused delays in processing license plate data, leading to bottlenecks at parking gates.
2. High Costs & Vendor Lock-In
The third-party ALPR system was expensive, with per-transaction fees, making the solution financially unsustainable as transaction volumes increased.
The company had no control over feature en
3. Need for a Frictionless Parking Experience
The existing system required manual intervention when ALPR validation failed, creating delays at entry and exit points.
First-time parkers had no seamless onboarding mechanism, leading to a poor user experience and lost revenue opportunities.
The client needed an in-house ALPR solution that could:
Detect and validate license plates in real-time using edge devices.
Integrate seamlessly with backend reservation and payment systems.
Enable gate vending automation, minimizing human intervention.
Continuously improve accuracy using AI-based retraining.
Solution
ekSource designed and deployed a fully integrated ALPR solution, combining edge computing, AI-powered license plate recognition, and cloud-based model retraining.
1. Edge-Based ALPR System for Real-Time Processing
NVIDIA Jetson Orin Nano edge devices were used for on-device AI inference, ensuring fast, real-time processing without requiring cloud dependency.
The YOLOv5 object detection model was fine-tuned for high-accuracy license plate recognition, optimized for parking environments.
Custom-trained CRNN-based OCR models improved character recognition accuracy, even under low-light and occluded conditions.
2. Seamless Backend Integration for Automated Gate Vending
The edge device was directly integrated with the company’s backend reservation and payment system, ensuring real-time validation of parking reservations.
If a license plate match was found, the system automatically opened the gate, allowing a seamless entry experience.
If no reservation was found, the system prompted the parker to create an account upon exiting, capturing new users for future bookings.
3. Cloud-Based Data Processing & Continuous Model Improvement
Apache Kafka/Kinesis was used for real-time data ingestion, enabling scalable processing across multiple parking locations.
AWS IoT Greengrass was used to remotely manage and update edge devices, ensuring over-the-air software updates for AI models.
AWS SageMaker was leveraged for periodic model retraining, improving plate detection accuracy over time by learning from misread captures.
4. Web-Based ALPR Dashboard for Operational Insights
A React-based dashboard provided real-time monitoring of parking activity, license plate captures, and reservation match rates.
The Flask/FastAPI backend facilitated user queries, gate logs, and reporting functionalities.
Prometheus & Grafana were used for system health monitoring, alerting the operations team to device failures or data inconsistencies.
Benefits
The AI-powered ALPR solution provided significant improvements in efficiency, accuracy, and cost savings:
Supports expansion across multiple parking locations, enabling enterprise-wide deployment.
Modular hardware integration allows for future camera upgrades without requiring software changes.
The system is flexible for future enhancements, such as real-time occupancy tracking and dynamic pricing models.
This PoC successfully demonstrated how an AI-powered ALPR and gate vending system can revolutionize parking operations by providing:
A seamless, fully automated parking experience without third-party vendor dependencies.
Real-time, high-accuracy ALPR processing using NVIDIA Jetson edge devices.
A cost-effective, scalable, and remotely managed ALPR infrastructure.
With this strong foundation, the company is now positioned to:
Scale AI-powered ALPR deployment across all parking locations.
Enhance AI-based predictive analytics for parking demand forecasting.
Implement dynamic pricing models based on real-time occupancy data.
By leveraging ekSource’s expertise in computer vision, AI model deployment, and cloud-based automation, the client successfully replaced a costly third-party ALPR system with a highly scalable, AI-driven in-house solution, improving operational efficiency and customer satisfaction.
ekSource continues to empower enterprises with AI solutions that drive automation, operational intelligence, and business transformation.
